With the increasing instability of the world situation and the participation of more participants in the aviation manufacturing supply chain, the risks faced by the management of the aviation manufacturing supply chain also increase. Therefore, this paper focuses on risk management in the aviation manufacturing supply chain network, using complex networks as a tool to study the identification of key nodes in the supply chain network, in order to help the aviation supply chain improve its risk resistance ability. By analyzing the current situation and characteristics of China"s aviation manufacturing supply chain network, the aviation manufacturing supply chain complex network is constructed and indicators are defined by proposing the formation mechanism of the supply chain and dividing the supply chain hierarchy. Three classical centrality algorithms, namely degree centrality, betweenness centrality and closeness centrality, and the traditional K-Shell method are weighted and improved. And in combination with the entropy-TOPISIS method, a WKC algorithm for identifying the key nodes of the supply chain for the weighted network is proposed. The feasibility and validity of this algorithm are verified by constructing a network to analyze a numerical example. The results indicate that the WKC algorithm proposed in this paper has scientific principles, low computational complexity, and provides a certain reference for risk management in the supply chain of high-end equipment manufacturing industries such as aviation manufacturing.